The activity of the group in the line of Control Engineering and Intelligent Systems is mainly devoted to study and develop new methods to cope with actual and future necessities of process monitoring and supervision. Main activity is focused on the efficient exploitation of data based on data mining and knowledge discovery principles: * Multivariate Statistical Process Control: Supervisory strategies for large number of variables. Dimensionality reduction and the development of fault detection and diagnosis mechanisms based on the process characterisation made from previous registers. * Case Based Diagnosis: Adaptation of Case Based Reasoning (CBR) methodology into the domain of dynamic process with emphasis on diagnosis. Definition of similarity criteria between signals, reuse of past experiences and definition of maintenance polices are in the scope of this line. * Qualitative representation of trends: Definition, formalization and development of numeric to qualitative interfaces. Representation of signals as sequences of episodes necessary to deal with knowledge based approaches. Hybridation of techniques (computational an